Data Description
The data we have chosen for this project is the Australian Road Deaths Database (ARDD) provided by the Australian Bureau of Infrastructure and Transport Research Economics (BITRE). The records are updated monthly from 1986 to 2021. Here is the link to the database : https://data.gov.au/dataset/ds-dga-5b530fb8-526e-4fbf-b0f6-aa24e84e4277/details.
There are two data files. The fatality data contains the demographic and details of people who have died within 30 days of the traffic accident due to injuries caused by an Australia road crash. The fatal crashes data contains the records for the crash, including information like the road type, and speed limit. The two data files can be connected by the crash ID. See Appendix for more detailed descriptions of each variable.
Research Questions:
Q1: What demographic has a higher rate of traffic accidents?
Q2: Ranking of vehicle types by number of accidents
Q3: How does the car accident fatality link with the district and accident type?
Q4: Is there any correlation between accidents and holiday? And why are some explanations for the relation(s) or lack thereof.
Q5 :Has accident rate decreased or increased within the past decade (2010- 2020)?
Q6: Possible correlations between number of fatalities and speed limit zone
Crash.ID State Month Year Crash.Type Number.Fatalities Bus.Involvement
1 20202001 Vic 12 2020 Multiple 1 No
2 20204057 SA 12 2020 Single 1 No
3 20203145 Qld 12 2020 Single 1 No
4 20203208 Qld 12 2020 Single 1 No
5 20203117 Qld 12 2020 Multiple 2 No
6 20201199 NSW 12 2020 Single 1 No
Heavy.Rigid.Truck.Involvement Articulated.Truck.Involvement Speed.Limit
1 No Yes 100
2 No No 100
3 No No 60
4 No No 100
5 No Yes 100
6 No No 50
National.LGA.Name.2017 Christmas.Period Easter.Period Time.of.day
1 Horsham (RC) Yes No Night
2 Tatiara (DC) No No Day
3 Sunshine Coast (R) No No Night
4 Bundaberg (R) Yes No Night
5 Cloncurry (S) Yes No Day
6 Upper Lachlan No No Day Crash.ID State Month Year Crash.Type Bus.Involvement
1 20203116 Qld 12 2020 Multiple No
2 20201210 NSW 12 2020 Single No
3 20203202 Qld 12 2020 Single No
4 20201093 NSW 12 2020 Single No
5 20203161 Qld 12 2020 Multiple No
6 20203179 Qld 12 2020 Multiple No
Heavy.Rigid.Truck.Involvement Articulated.Truck.Involvement Speed.Limit
1 No No 60
2 No No 100
3 No No 100
4 No No 100
5 No No 70
6 No No 100
Road.User Gender Age National.LGA.Name.2017 Christmas.Period
1 Motorcycle rider Male 28 Cairns (R) No
2 Passenger Male 89 Walcha Yes
3 Driver Male 21 Charters Towers (R) Yes
4 Driver Male 81 Walcha No
5 Driver Female 66 Moreton Bay (R) No
6 Passenger Male 79 Lockyer Valley (R) No
Easter.Period Age.Group Time.of.day
1 No 26_to_39 Night
2 No 75_or_older Day
3 No 17_to_25 Day
4 No 75_or_older Night
5 No 65_to_74 Night
6 No 75_or_older DayData Analysis
##Q1:
##Q2:
##Q3:
Question 3
#How does the car accident fatality link with the district and accident type?
Column
Table 1
First of all, we group the data by state and the type of car which have involved in the fatal accidents.# A tibble: 6 x 2
# Groups: State [6]
State Bus_Involved
<chr> <int>
1 ACT 4
2 NSW 75
3 NT 6
4 Qld 43
5 SA 13
6 Tas 7# A tibble: 6 x 2
# Groups: State [6]
State Heavytruck_Involved
<chr> <int>
1 ACT 3
2 NSW 266
3 NT 5
4 Qld 144
5 SA 53
6 Tas 27# A tibble: 6 x 2
# Groups: State [6]
State Articulated_truck_Involved
<chr> <int>
1 ACT 6
2 NSW 344
3 NT 15
4 Qld 278
5 SA 104
6 Tas 29Table2
# A tibble: 6 x 3
# Groups: State [2]
State Type Count
<chr> <chr> <int>
1 ACT Bus_Involved 4
2 ACT Heavytruck_Involved 3
3 ACT Articulated_truck_Involved 6
4 NSW Bus_Involved 75
5 NSW Heavytruck_Involved 266
6 NSW Articulated_truck_Involved 344In this table, we have got the count of different type of fatal accidents happened group by different states. This data is in long format which will be easier for us to plot the bar chart for better visualization.
Chart 1
From the graph above: -NSW is the state with highest number of fatal accidents -follow by Qld and Vic.
In all the states: -more than half of the total fatal accidents with articulated truck involved. -Accidents with Heavy Truck involved account for the second large portion of the total accidents -follow by bus involved accidents.
Column
Then, we group the data by states and the type of Road Users which have involved in the fatal accidents.
# A tibble: 6 x 3
# Groups: State, Road.User [6]
State Road.User Count
<chr> <chr> <int>
1 ACT Driver 47
2 ACT Motorcycle pillion passenger 1
3 ACT Motorcycle rider 24
4 ACT Passenger 16
5 ACT Pedal cyclist 7
6 ACT Pedestrian 11Chart 2
From the graph above:
In all the states: -more than half of the total fatal accidents with drivers involved. -Accidents with Passenger involved account for the second large portion of the total accidents -follow by motorcycle rider and then pedestrian involved accidents.
Then, we group the data by the crash type and count the number of it.
# A tibble: 6 x 3
# Groups: State, Crash.Type [6]
State Crash.Type Count
<chr> <chr> <int>
1 ACT Multiple 57
2 ACT Single 49
3 NSW Multiple 1783
4 NSW Single 2112
5 NT Multiple 129
6 NT Single 333Chart 3
From the graph above:
In all the states except ACT and Tas: -all of the states have more single car crash than multiple car crash in terms of fatal car crashes.
How does the car accident fatality link with the district?# A tibble: 6 x 3
# Groups: State, National.LGA.Name.2017 [6]
State National.LGA.Name.2017 n
<chr> <chr> <int>
1 Qld <NA> 1786
2 NSW <NA> 1778
3 Vic <NA> 1638
4 WA <NA> 954
5 SA <NA> 415
6 NT <NA> 220# A tibble: 6 x 3
# Groups: State, National.LGA.Name.2017 [6]
State National.LGA.Name.2017 n
<chr> <chr> <int>
1 Qld Brisbane (C) 87
2 NSW Central Coast 82
3 Qld Gold Coast (C) 68
4 Qld Moreton Bay (R) 62
5 NSW Lake Macquarie 56
6 NSW Shoalhaven 55From the table above: -first table contain value with NA -in this table, we don’t have detail district information for some cases. -However, in general, we could see that QLD, NSW, and Vic, these 3 states are top 3 in terms of number of fatal accidents. ##-***Be aware, this count do not reflect the actual ranking for the number of accidents.
-second table contain value without NA -in this table, we can conclude: +Brisbane in Qld is the district which has the most fatal car accidents happened, which has 87 cases within this 10 years. +Follow by Central Coast in NSW which is 82 fatal car accidents happened +The third one is Gold Coast which has 68 cases in this 10 years.